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--- |
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license: mit |
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base_model: microsoft/phi-2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: V0316MP2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# V0316MP2 |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0962 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 20 |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.5399 | 0.09 | 10 | 2.3219 | |
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| 2.1738 | 0.17 | 20 | 1.8070 | |
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| 1.6126 | 0.26 | 30 | 1.2246 | |
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| 1.1047 | 0.34 | 40 | 0.7910 | |
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| 0.6789 | 0.43 | 50 | 0.3123 | |
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| 0.3195 | 0.51 | 60 | 0.1536 | |
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| 0.2157 | 0.6 | 70 | 0.1208 | |
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| 0.1791 | 0.68 | 80 | 0.1139 | |
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| 0.16 | 0.77 | 90 | 0.1100 | |
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| 0.1628 | 0.85 | 100 | 0.1076 | |
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| 0.1556 | 0.94 | 110 | 0.1066 | |
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| 0.1509 | 1.02 | 120 | 0.1057 | |
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| 0.1575 | 1.11 | 130 | 0.1040 | |
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| 0.1502 | 1.19 | 140 | 0.1038 | |
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| 0.148 | 1.28 | 150 | 0.1024 | |
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| 0.1478 | 1.37 | 160 | 0.1019 | |
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| 0.1469 | 1.45 | 170 | 0.1015 | |
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| 0.1339 | 1.54 | 180 | 0.1008 | |
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| 0.1433 | 1.62 | 190 | 0.1002 | |
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| 0.1408 | 1.71 | 200 | 0.0993 | |
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| 0.1391 | 1.79 | 210 | 0.0987 | |
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| 0.1411 | 1.88 | 220 | 0.0980 | |
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| 0.1345 | 1.96 | 230 | 0.0975 | |
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| 0.1422 | 2.05 | 240 | 0.0968 | |
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| 0.1374 | 2.13 | 250 | 0.0970 | |
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| 0.1341 | 2.22 | 260 | 0.0970 | |
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| 0.1346 | 2.3 | 270 | 0.0968 | |
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| 0.1412 | 2.39 | 280 | 0.0966 | |
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| 0.1339 | 2.47 | 290 | 0.0959 | |
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| 0.1395 | 2.56 | 300 | 0.0961 | |
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| 0.1376 | 2.65 | 310 | 0.0961 | |
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| 0.1384 | 2.73 | 320 | 0.0960 | |
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| 0.1374 | 2.82 | 330 | 0.0958 | |
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| 0.1295 | 2.9 | 340 | 0.0959 | |
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| 0.1298 | 2.99 | 350 | 0.0962 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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